Evaluation of the Stability of the Darbandikhan Dam after the 12 November 2017 Mw 7.3 Sarpol-e Zahab (Iran–Iraq Border) Earthquake

Al-Husseinawi, Yasir; Li, Zhenhong; Clarke, Peter J.; Edwards, Stuart

doi:10.3390/rs10091426

Cited by 22 publications

(19 citation statements)

References 52 publications

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“…Previous work (e.g., [2,36,41]) highlighted the capability of satellite techniques for dam monitoring. This research aims to emphasise that comprehensive monitoring is achievable using satellite techniques.…”

Section: Discussionmentioning

confidence: 99%

“…The monitoring of dam displacements plays a crucial role in the detection of unsafe conditions, requiring appropriate management actions and/or counteractive measures from the early stages [1]. Indeed, the early detection of a dam instability should constitute a key component of any dam maintenance plan and could lead to structural stabilisation to prevent any initial warning from turning into a disaster [2].…”

Section: Introductionmentioning

confidence: 99%

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Toward a Comprehensive Dam Monitoring: On-Site and Remote-Retrieved Forcing Factors and Resulting Displacements (GNSS and PS–InSAR)

et al. 2021

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Many factors can influence the displacements of a dam, including water level variability and environmental temperatures, in addition to the dam composition. In this work, optical-based classification, thermal diachronic analysis, and a quasi-PS (Persistent Scatter) Interferometric SAR technique have been applied to determine both forcing factors and resulting displacements of the crest of the Castello dam (South Italy) over a one-year time period. The dataset includes Sentinel-1A images acquired in Interferometric Wide swath mode using the Terrain Observation with Progressive Scans SAR (TOPSAR); Landsat 8 Thermal Infrared Sensor (TIRS) thermal images, and Global Navigation Satellite System (GNSS) for interpreting the motion of the top of the dam retrieved via interferometry. Results suggest that it is possible to monitor both dam water level and temperature periodic forcing factors and resulting displacements via a synergistic use of different satellite images.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Toward a Comprehensive Dam Monitoring: On-Site and Remote-Retrieved Forcing Factors and Resulting Displacements (GNSS and PS–InSAR)

et al. 2021

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“…While monitoring of individual infrastructure is critical, the regional-scale monitoring of infrastructure is hypercritical for land use planning and sustainable development. Studies have shown the application of satellite-based Interferometric Synthetic Aperture Radar (InSAR) for monitoring bridges and critical infrastructure as well as regional-scale displacement from tectonics and other processes [8][9][10][11][12]. This study builds on those efforts to demonstrate how InSAR based (particularly Persistent Scatterer Interferometry (PSI)) monitoring and Geographic Information System (GIS) based analysis can be helpful to understand the performance of an individual infrastructure as well as evaluate whether regional scale processes control these performances.…”

Section: Introductionmentioning

confidence: 97%

Monitoring the Impact of Groundwater Pumping on Infrastructure Using Geographic Information System (GIS) and Persistent Scatterer Interferometry (PSI)

2018

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Transportation infrastructure is critical for the advancement of society. Bridges are vital for an efficient transportation network. Bridges across the world undergo variable deformation/displacement due to the Earth’s dynamic processes. This displacement is caused by ground motion, which occurs from many natural and anthropogenic events. Events causing deformation include temperature fluctuation, subsidence, landslides, earthquakes, water/sea level variation, subsurface resource extraction, etc. Continual deformation may cause bridge failure, putting civilians at risk, if not managed properly. Monitoring bridge displacement, large and small, provides evidence of the state and health of the bridge. Traditionally, bridge monitoring has been executed through on-site surveys. Although this method of bridge monitoring is systematic and successful, it is not the most efficient and cost-effective. Through technological advances, satellite-based Persistent Scatterer Interferometry (PSI) and Geographic Information Systems (GIS) have provided a system for analyzing ground deformation over time. This method is applied to distinguish bridges that are more at risk than others by generating models that display the displacement at various locations along each bridge. A bridge’s health and its potential risk can be estimated upon analysis of measured displacement rates. In return, this process of monitoring bridges can be done at much faster rates; saving time, money and resources. PSI data covering Oxnard, California, revealed both bridge displacement and regional ground displacement. Although each bridge maintained different patterns of displacement, many of the bridges within the Oxnard area displayed an overall downward movement matching regional subsidence trends observed in the area. Patterns in displacement-time series plots provide evidence for two types of deformation mechanisms. Long-term downward movements correlate with the relatively large regional subsidence observed using PSI in Oxnard. Thermal dilation from seasonal temperature changes may cause short-term variabilities unique to each bridge. Overall, it may be said that linking geologic, weather, and groundwater patterns with bridge displacement has shown promise for monitoring transportation infrastructure and more importantly differentiating between regional subsidence and site-specific displacements.

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“…Also, correlation between changes of reservoir surface, obtained by remote sensing methods, with obtained GNSS displacements was calculated in this study and results showed weak positive correlation between tested variables [7]. Levelling, GPS measurements and SAR images are used to evaluate stability of the Darbandikhan dam (Iraq) after high magnitude earthquake in research conducted by Al-Husseinawi et al (2018). Their research concludes that SAR images of the post-seismic dam deformation are useful to inform maintenance plans, but terrestrial surveys are still essential in the case of large-gradient deformation during earthquakes [8].…”

mentioning

confidence: 96%

“…Levelling, GPS measurements and SAR images are used to evaluate stability of the Darbandikhan dam (Iraq) after high magnitude earthquake in research conducted by Al-Husseinawi et al (2018). Their research concludes that SAR images of the post-seismic dam deformation are useful to inform maintenance plans, but terrestrial surveys are still essential in the case of large-gradient deformation during earthquakes [8].…”

mentioning

confidence: 99%

Multistage Cascade Predictor of Structural Elements Movement in the Deformation Analysis of Large Objects Based on Time Series Influencing Factors

Hamzić

Avdagić

Besic

2020

IJGI

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Hydropower dam displacement is influenced by various factors (dam ageing, reservoir water level, air, water, and concrete temperature), which cause complex nonlinear behaviour that is difficult to predict. Object deformation monitoring is a task of geodetic and civil engineers who use different instruments and methods for measurements. Only geodetic methods have been used for the object movement analysis in this research. Although the whole object is affected by the influencing factors, different parts of the object react differently. Hence, one model cannot describe behaviour of every part of the object precisely. In this research, a localised approach is presented—two individual models are developed for every point strategically placed on the object: one model for the analysis and prediction in the direction of the X axis and the other for the Y axis. Additionally, the prediction of horizontal dam movement is not performed directly from measured values of influencing factors, but from predicted values obtained by machine learning and statistical methods. The results of this research show that it is possible to perform accurate short-term time series dam movement prediction by using machine learning and statistical methods and that the only limiting factor for improving prediction length is accurate weather forecast.

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Evaluation of the Stability of the Darbandikhan Dam after the 12 November 2017 Mw 7.3 Sarpol-e Zahab (Iran–Iraq Border) Earthquake

Cited by 22 publications

References 52 publications

Toward a Comprehensive Dam Monitoring: On-Site and Remote-Retrieved Forcing Factors and Resulting Displacements (GNSS and PS–InSAR)

Toward a Comprehensive Dam Monitoring: On-Site and Remote-Retrieved Forcing Factors and Resulting Displacements (GNSS and PS–InSAR)

Monitoring the Impact of Groundwater Pumping on Infrastructure Using Geographic Information System (GIS) and Persistent Scatterer Interferometry (PSI)

Multistage Cascade Predictor of Structural Elements Movement in the Deformation Analysis of Large Objects Based on Time Series Influencing Factors

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